Text Classification
Transformers
Safetensors
English
roberta
facebook
sentiment
customer-support
huggingface
fine-tuned
Eval Results (legacy)
text-embeddings-inference
Instructions to use harshithan/fb-post-classifier-roberta_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harshithan/fb-post-classifier-roberta_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harshithan/fb-post-classifier-roberta_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harshithan/fb-post-classifier-roberta_v1") model = AutoModelForSequenceClassification.from_pretrained("harshithan/fb-post-classifier-roberta_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7adf925febafa42fcc429be824a53536713f3dd9fede563a3cd44137452e2a95
- Size of remote file:
- 5.24 kB
- SHA256:
- f827931f40f2a4102434da7ef40407c4f3f2ebb347681f6b9acfe005f7b51ac6
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